Photoacoustic flow velocity imaging based on complex field decorrelation

Photoacoustic (PA) imaging can be used to monitor flowing blood inside the microvascular and capillary bed. Ultrasound speckle decorrelation based velocimetry imaging was previously shown to accurately estimate blood flow velocity in mouse brain (micro-)vasculature. Translating this method to photoacoustic imaging will allow simultaneous imaging of flow velocity and extracting functional parameters like blood oxygenation. In this study, we use a pulsed laser diode and a quantitative method based on normalized first order field autocorrelation function of PA field fluctuations to estimate flow velocities in an ink tube phantom and in the microvasculature of the chorioallantoic membrane of a chicken embryo. We demonstrate how the decorrelation time of signals acquired over frames are related to the flow speed and show that the PA flow analysis based on this approach is an angle independent flow velocity imaging method.

Automated summary

Photoacoustic (PA) imaging can monitor flowing blood in microvascular and capillaries, accurately estimate blood flow velocity, and extract functional parameters. This study demonstrates a quantitative method to estimate flow velocities based on normalized first order field autocorrelation function, showing an angle independent flow velocity imaging method. The decorrelation time of signals acquired over frames is related to flow speed.